Chapter 3: Evaluating Regression Model Fit and Interpreting Results

In this section

• Analyzing Goodness of Fit: R-Squared, Adjusted R-Squared
  Discover how R-Squared and Adjusted R-Squared gauge a regression model’s explanatory power in financial applications, including formula derivations, visual aids, interpretation guidance, and real-world examples to enhance exam performance.
• Analysis of Variance (ANOVA) in Multiple Regression
  Understand how ANOVA decomposes total variation in multiple regression, evaluates model significance via the F-test, and offers key insights for financial applications and the CFA Level II exam.
• Hypothesis Testing for Individual and Joint Coefficients
  Explore in-depth how to employ t-tests and partial F-tests for validating regression coefficients, understand economic versus statistical significance, and master critical exam applications for CFA Level II.
• Constructing and Interpreting Confidence Intervals
  Learn how to build, interpret, and apply confidence intervals for regression coefficients in investment analysis. This section provides thorough coverage of interval estimates, significance levels, and practical techniques for the CFA Level II exam.
• Forecasting with a Multiple Regression Model
  Discover how to generate accurate forecasts using regression coefficients, evaluate forecast uncertainty with confidence and prediction intervals, and gauge model performance through in-sample vs. out-of-sample testing.
• Vignette-Based Exercises and Solutions
  Explore how to apply regression model fit and interpretation in realistic CFA vignette-style scenarios, with detailed strategies, calculations, and solutions.
• Model Selection Criteria and Diagnostics
  Explore R², adjusted R², AIC, BIC, and Mallow's Cp for robust model selection, plus practical residual diagnostics and exam-relevant tips for CFA Level II candidates.